A metabolic energy expenditure model with a continuous first derivative and its application to predictive simulations of gait
Koelewijn A, Dorschky E, van den Bogert AJ (2018)
Publication Language: English
Publication Type: Journal article, Original article
Publication year: 2018
Journal
Book Volume: 21
Pages Range: 521 - 531
Journal Issue: 8
DOI: 10.1080/10255842.2018.1490954
Abstract
Whether humans minimize metabolic energy in gait is unknown. Gradient-based optimization could be used to predict gait without using walking data but requires a twice differentiable metabolic energy model. Therefore, the metabolic energy model of Umberger et al. was adapted to be twice differentiable. Predictive simulations of a reaching task and gait were solved using this continuous model and by minimizing effort. The reaching task simulation showed that energy minimization predicts unrealistic movements when compared to effort minimization. The predictive gait simulations showed that objectives other than metabolic energy are also important in gait.
Authors with CRIS profile
Anne Koelewijn
Juniorprofessur für Informatik (Stiftungsprofessur)
Eva Dorschky
Lehrstuhl für Informatik 14 (Machine Learning and Data Analytics)
Additional Organisation(s)
Machine Learning and Data Analytics Lab
Juniorprofessur für Computational Movement Science (Stiftungsprofessur)
Involved external institutions
United States (USA) (US)How to cite
APA:
Koelewijn, A., Dorschky, E., & van den Bogert, A.J. (2018). A metabolic energy expenditure model with a continuous first derivative and its application to predictive simulations of gait. Computer Methods in Biomechanics and Biomedical Engineering, 21(8), 521 - 531. https://dx.doi.org/10.1080/10255842.2018.1490954
MLA:
Koelewijn, Anne, Eva Dorschky, and Antonie J. van den Bogert. "A metabolic energy expenditure model with a continuous first derivative and its application to predictive simulations of gait." Computer Methods in Biomechanics and Biomedical Engineering 21.8 (2018): 521 - 531.
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